Reinforcement Learning-Based Spectrum Management for Cognitive Radio Networks: A Literature Review and Case Study

2019 ◽  
pp. 1849-1886
Author(s):  
Marco Di Felice ◽  
Luca Bedogni ◽  
Luciano Bononi
Keyword(s):  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Literature Review ◽  
Cognitive Radio Networks ◽  
Spectrum Management ◽  
Radio Networks

scholarly journals Distributed Spectrum Management in Cognitive Radio Networks by Consensus-Based Reinforcement Learning

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2970
Author(s):  
Dejan Dašić ◽  
Nemanja Ilić ◽  
Miljan Vučetić ◽  
Miroslav Perić ◽  
Marko Beko ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Channel Selection ◽  
Spectrum Management ◽  
Radio Networks ◽  
Selection Strategy ◽  
Distributed Spectrum Sensing ◽  
The Individual

In this paper, we propose a new algorithm for distributed spectrum sensing and channel selection in cognitive radio networks based on consensus. The algorithm operates within a multi-agent reinforcement learning scheme. The proposed consensus strategy, implemented over a directed, typically sparse, time-varying low-bandwidth communication network, enforces collaboration between the agents in a completely decentralized and distributed way. The motivation for the proposed approach comes directly from typical cognitive radio networks’ practical scenarios, where such a decentralized setting and distributed operation is of essential importance. Specifically, the proposed setting provides all the agents, in unknown environmental and application conditions, with viable network-wide information. Hence, a set of participating agents becomes capable of successful calculation of the optimal joint spectrum sensing and channel selection strategy even if the individual agents are not. The proposed algorithm is, by its nature, scalable and robust to node and link failures. The paper presents a detailed discussion and analysis of the algorithm’s characteristics, including the effects of denoising, the possibility of organizing coordinated actions, and the convergence rate improvement induced by the consensus scheme. The results of extensive simulations demonstrate the high effectiveness of the proposed algorithm, and that its behavior is close to the centralized scheme even in the case of sparse neighbor-based inter-node communication.

An Energy Efficient Spectrum Aware Routing for Cognitive Radio Networks (CRNs)

2020 ◽  
Vol 10 ◽  
Author(s):  
Dileep Reddy Bolla ◽  
Jijesh J J ◽  
Mahaveer Penna ◽  
Shiva Shankar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Research Work ◽  
Spectrum Management ◽  
Residual Energy ◽  
Radio Networks ◽  
Traffic Load ◽  
The Impact

Back Ground/ Aims:: Now-a-days in the Wireless Communications some of the spectrum bands are underutilized or unutilized; the spectrum can be utilized properly by using the Cognitive Radio Techniques using the Spectrum Sensing mechanisms. Objectives:: The prime objective of the research work carried out is to achieve the energy efficiency and to use the spectrum effectively by using the spectrum management concept and achieve better throughput, end to end delay etc., Methods:: The detection of the spectrum hole plays a vital role in the routing of Cognitive Radio Networks (CRNs). While detecting the spectrum holes and the routing, sensing is impacted by the hidden node issues and exposed node issues. The impact of sensing is improved by incorporating the Cooperative Spectrum Sensing (CSS) techniques. Along with these issues the spectrum resources changes time to time in the routing. Results:: All the issues are addressed with An Energy Efficient Spectrum aware Routing (EESR) protocol which improves the timeslot and the routing schemes. The overall network life time is improved with the aid of residual energy concepts and the overall network performance is improved. Conclusion:: The proposed protocol (EESR) is an integrated system with spectrum management and the routing is successfully established to communication in the network and further traffic load is observed to be balanced in the protocol based on the residual energy in a node and further it improves the Network Lifetime of the Overall Network and the Individual CR user, along with this the performance of the proposed protocol outperforms the conventional state of art routing protocols.

scholarly journals Efficient Spectrum Management Techniques for Cognitive Radio Networks for Proximity Service

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 43795-43805 ◽  
Author(s):  
S. Nandakumar ◽  
T. Velmurugan ◽  
Utthara Thiagarajan ◽  
Marimuthu Karuppiah ◽  
Mohammad Mehedi Hassan ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Spectrum Management ◽  
Radio Networks ◽  
Management Techniques ◽  
Proximity Service
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